Task 1: Spatial Data Visualization

Spatial Visualization of California Oil Spills in 2008

Shayan Kaveh
2022-03-03
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knitr::opts_chunk$set(echo = TRUE, warning = F, message = F)
library(tidyverse)
library(here)
library(broom)
library(sf)
library(tmap)
library(plotly)

Overview

This analysis visualizes data from the Oil Spill Prevention and Response (OSPR) Incident Tracking database, collected by OSPR Field Response team members. The analysis looks at overall oil spills and a closer look at inland oil spills in 2008.

Data Source: Lampinen, Mark (2009). Oil Spill Incident Tracking [ds394]. California Department of Fish and Game, Office of Spill Prevention and Response. https://map.dfg.ca.gov/metadata/ds0394.html?5.108.39

Analysis

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ca_counties_sf <- read_sf(here("_posts", "2022-03-05-spatial-data", "data", "ca_counties", "CA_Counties_TIGER2016.shp")) %>% 
  janitor::clean_names() %>% 
  select(county_name = name)

# st_crs(ca_counties_sf) ### WGS84, epsg: 3857

ca_oil_sf <- read_sf(here("_posts", "2022-03-05-spatial-data", "data", "ds394", "ds394.shp")) %>% 
  janitor::clean_names()

# st_crs(ca_oil_sf) ### NAD83, epsg: 3310

oil_3857_sf <- st_transform(ca_oil_sf, st_crs(ca_counties_sf))

# st_crs(oil_3857_sf) 
#wooh it's in wgs 84 now

All oil spills (2008)

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tmap_mode(mode = "view")

tm_shape(ca_counties_sf) +
  tm_fill() +
  tm_basemap(c(StreetMap = "OpenStreetMap",
               TopoMap = "OpenTopoMap")) +
  tm_borders() +
  tm_polygons(alpha = 0) + # remove county fill
  tm_shape(ca_oil_sf) +
  tm_dots(col = "indianred")

Figure 1. Interactive California map representing all oil spills in 2008


Oil spills by county

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oil_ca_sf <- ca_counties_sf %>% 
  st_join(oil_3857_sf)
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oil_counts_sf <- oil_ca_sf %>% 
  group_by(county_name) %>% 
  filter(inlandmari %in% "Inland") %>% 
  summarize(sum_spills = sum(!is.na(oesnumber))) # summarize total oil spills by county

# head(oil_counts_sf)
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chloropleth <- ggplot(data = oil_counts_sf) +
  geom_sf(aes(fill = sum_spills), color = "gray", size = 0.5) +
  scale_fill_gradientn(colors = c("ivory", "lightcoral", "indianred4")) +
  labs(fill = "Number of inland oil spills by county") +
  theme_void() 

ggplotly(chloropleth, tooltip = c("County", "sum_spills"))

Figure 1: Figure 2. Total number of inland oil spills summarized by county